Genomic evaluation with multibreed and crossbred data

[Display omitted] •We found low accuracy of genomic evaluation of crossbreds based on purebred data.•We found higher accuracy for crossbreds based on crossbred data.•Use of putative sequence variants had a small impact on genomic accuracy. Several types of multibreed genomic evaluation are in use. These include evaluation of crossbreds based on purebred SNP effects, joint evaluation of all purebreds and crossbreds with a single additive effect, and treating each purebred and crossbred group as a separate trait. Additionally, putative quantitative trait nucleotides can be exploited to increase the accuracy of prediction. Existing studies indicate that the prediction of crossbreds based on purebred data has low accuracy, that a joint evaluation can potentially provide accurate evaluations for crossbreds but could lower accuracy for purebreds compared with single-breed evaluations, and that the use of putative quantitative trait nucleotides only marginally increases the accuracy. One hypothesis is that genomic selection is based on estimation of clusters of independent chromosome segments. Subsequently, predicting a particular group type would require a reference population of the same type, and crosses with same breed percentage but different type (F1 vs. F2) would, at best, use separate reference populations. The genomic selection of multibreed population is still an active research topic.